The purpose of this study is to perform the quantitative diagnosis of drought hazard degree using multi-source remote sensing data. Hazard degree is the basic function for disaster risk assessment and loss assessment. Quantitative diagnosis of drought hazard degree is essential to decision-making of drought early warning and emergency relief in practice. The currently used diagnosis methods are based on disaster loss and drought indices. The response process and impacts of drought in different crop growth stages were ignored in these methods. So, the instructions were not dynamic and real time. This study investigated the drought hazard degree diagnosing of winter wheat based on continuous multi-source remote sensing imagery and comprehensive ground-based observations. The resulted indicated that the correlation is high and drought hazard degree is suitable and sensitive to reveal drought disaster-forming environment evolution, drought formation mechanism and drought influence.

Date Published: 14 December 2015
PDF: 6 pages
Proc. SPIE 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 98151P (14 December 2015); doi: 10.1117/12.2205636

Published in SPIE Proceedings Vol. 9815:
MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Jianguo Liu; Hong Sun, Editor(s)